PlusAI

Reinforcement Learning Planning Research Intern

PlusAI · Santa Clara, CA
Santa Clara, CA was $39K–$135K Intern Closed
Applications are closed for this role. It was originally posted 2026-05-22. It’s no longer accepting applicants — see roles PlusAI is still hiring for →, or browse the live openings below.
Salary
$39K–$135K
Type
Internship
Experience
1+ yr

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

Your opportunities joining PlusAI
Work, learn and grow in a highly future-oriented, innovative and dynamic field.
Wide range of opportunities for personal and professional development.
Catered free lunch, unlimited snacks and beverages.
Highly competitive salary and benefits package, including 401(k) plan.

  • Conduct groundbreaking research with the potential to strongly impact Plus’s autonomous driving products, leading to publishable results. Key focus area for this internship will be reinforcement learning to generate safe trajectories for autonomous driving.
  • Develop and benchmark cutting-edge techniques in deep learning.
  • Collaborate with team members to optimize and seamlessly integrate developed techniques into the production perception/AV stack.
  • Pursuing MS or PhD in CS, EE, mathematics, statistics or related field
  • Thorough understanding of reinforcement learning
  • 1-2 years experience with implementing and training models in at least one deep learning framework (PyTorch, Tensorflow, Jax
  • Past experiences in design, implementation and training of deep reinforcement learning models
  • Past experiences in projects related to autonomous driving
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Applications closed